Update app.py

app.py

@@ -11,7 +11,7 @@ import gradio as grad
 # text2text_tkn = AutoTokenizer.from_pretrained('deep-learning-analytics/wikihow-t5-small')
 # mdl = AutoModelWithLMHead.from_pretrained('deep-learning-analytics/wikihow-t5-small')
 
-# translate
+# translate, sentiment
 text2text_tkn = T5Tokenizer.from_pretrained('t5-small')
 mdl = T5ForConditionalGeneration.from_pretrained('t5-small')
 
@@ -43,7 +43,15 @@ def text2text_summary(para):
     return response
 
 def text2text_translate(text):
-    inp = "translate English to Korean:: " + text
+    inp = "translate English to German:: " + text
+    enc = text2text_tkn(inp, return_tensors = 'pt')
+    tokens = mdl.generate(**enc)
+    response = text2text_tkn.batch_decode(tokens)
+
+    return response
+
+def text2text_sentiment(text):
+    inp = "sst2 sentence: " + text
     enc = text2text_tkn(inp, return_tensors = 'pt')
     tokens = mdl.generate(**enc)
     response = text2text_tkn.batch_decode(tokens)
@@ -60,14 +68,19 @@ def text2text_translate(text):
 # out = grad.Textbox(lines = 1, label = 'Summary')
 
 # tranlate
+# para = grad.Textbox(lines = 1, label = 'English Text', placeholder = 'Text in English')
+# out = grad.Textbox(lines = 1, label = 'German Translation')
+
+# sentiment
 para = grad.Textbox(lines = 1, label = 'English Text', placeholder = 'Text in English')
-out = grad.Textbox(lines = 1, label = 'Korean Translation')
+out = grad.Textbox(lines = 1, label = 'Sentiment')
 
 grad.Interface(
    # text2text,
     # inputs = [context, ans],
     # text2text_summary,
-    text2text_translate,
+    # text2text_translate,
+    text2text_sentiment,
     inputs = para,
     outputs = out
 ).launch()